Sql developer állások V. kerületben (adatbázisszakértő)

• Támogatod a teljesítménymenedzsment rendszer kialakítását és működtetését, részt veszel a folyamatok felmérésében és optimalizálásában.
• Adatokat gyűjtesz, tisztítasz, rendszerezel és elemzel, valamint rendszeres és eseti riportokat, vezetői összefoglalókat és Power BI dashboardokat készítesz.

• Leading a data engineering team comprising 5-6 consultants
• Overseeing project delivery
• Managing and mentoring the team
• Ensuring successful execution of data engineering projects
• Ensuring successful execution of ML/MLOps projects
• Ensuring successful execution of cloud migration projects

• Maintaining and evolving data structures
• Building new ETL flows and maintaining or improving existing ones
• Designing new data structures and data modelling concepts
• Ensuring data quality by verifying data consistency and accuracy
• Creating data validation methods

• Maintaining and evolving data structures
• Building new ETL flows and maintaining or improving existing ones
• Designing new data structures and data modelling concepts
• Ensuring data quality by verifying data consistency and accuracy
• Creating data validation methods

• Establish data feeds with custodian banks, data vendors, and other service providers
• Support senior leadership, clients, and the broader Data Team in executing analyses and providing data-driven answers to questions
• Fully automate and centralize existing data integration processes

• Design and build scalable, reusable frameworks and services for data ingestion, transformation, and processing
• Develop and maintain the platform’s core capabilities such as orchestration, data quality validation, and schema management tools

• PostgreSQL adatbázisok üzemeltetése
• Telepítések, verzióváltások
• Adatbázis teljesítmény elemzése, hangolások
• Riasztási események kezelése
• Mentési és visszatöltési feladatok
• Kapcsolattartás az alapinfrastruktúra üzemeltető csoportokkal (OS, Hálózat, Backup)

• Delivery of complex data engineering projects individually or by leading small delivery teams
• Management of customer relationships alone or in collaboration with a Project Manager
• Support of pre-sales process
• Mentoring of more junior engineers
• Contribution to hiring best-in-class data talent

Performing tasks related to the position....

• Delivery on complex data engineering projects across industries
• Leading small delivery teams
• Managing customer relationships alone or with a Project Manager
• Mentoring more junior engineers
• Evaluating the quality of junior engineers' work
• Contributing to hiring best-in-class data engineers

• Maintaining and evolving data structures
• Building new ETL flows and maintaining or improving existing ones
• Designing new data structures and data modelling concepts
• Ensuring data quality by verifying data consistency and accuracy
• Creating data validation methods

• Fejlesztés, karbantartás és támogatás felhőalapú adatműveleti infrastruktúrán és termelési adatcsatornákon
• Tervezés, megvalósítás, működtetés és optimalizálás Azure-alapú adat szolgáltatások és Databricks munkaterhelések terén

• Ownership of data engineering features, architecture, and code quality
• Design, implementation, and maintenance of Databricks-based data pipelines and workflows
• Building and optimization of ETL/ELT processes using Apache Spark on Databricks

• Implementation and support of VB.NET based software solution
• Participation in the run and maintain team

Web alapú vállalatirányítási rendszer fejlesztése...

• Design and build scalable, reusable frameworks and services for data ingestion, transformation, and processing
• Develop and maintain the platform’s core capabilities such as orchestration, data quality validation, and schema management tools

• Dashboard development with Power BI to visualize sustainability data and metrics
• Data integration from internal databases, external APIs, and third-party platforms
• Client reporting collaboration with sustainability team for customized visual analytics

• Design and implement data fabric architecture across heterogeneous data sources and platforms
• Develop scalable ETL/ELT pipelines for batch and real-time data integration
• Integrate structured and unstructured data from databases, APIs, SaaS applications, data lakes, and enterprise systems

• Ownership of data models and storage architecture behind AI systems across relational, graph, and retrieval-oriented data
• Building and operating APIs, backend services, and pipelines to keep data current and accessible

• Microsoft SQL Server operation including maintenance, migrations, administration, configuration
• Support for developers, testers and DevOps engineers about best practices in database operation